1. Field of the Invention
This invention relates to quantum computing and, in particular, to a control system for performing operations on a quantum qubit.
2. Description of Related Art
Research on what is now called quantum computing traces back to Richard Feynman, See, e.g., R. Feynman, Int. J. Theor. Phys., 21, 467-488 (1982). Feynman noted that quantum systems are inherently difficult to simulate with classical (i.e., conventional, non-quantum) computers, but that this task could be accomplished by observing the evolution of another quantum system. In particular, solving a theory for the behavior of a quantum system commonly involves solving a differential equation related to the Hamiltonian of the quantum system. Observing the behavior of the quantum system provides information regarding the solutions to the equation.
Further efforts in quantum computing were initially concentrated on “software development” or building of the formal theory of quantum computing. Software development for quantum computing involves attempting to set the Hamiltonian of a quantum system to correspond to a problem requiring solution. Milestones in these efforts were the discoveries of the Shor and Grover algorithms. See, e.g., P. Shor, SIAM J. of Comput., 26:5, 1484-1509 (1997); L. Grover, Proc. 28th STOC, 212-219 (1996); and A. Kitaev, LANL preprint quant-ph/9511026 (1995). In particular, the Shor algorithm permits a quantum computer to factorize large numbers efficiently. In this application, a quantum computer could render obsolete all existing “public-key” encryption schemes. In another application, quantum computers (or even a smaller scale device such as a quantum repeater) could enable absolutely safe communication channels where a message cannot be intercepted without being destroyed in the process. See, e.g., H. J. Briegel, W. Dur, J. I. Cirac, P. Zoller, LANL preprint quant-ph/9803056 (1998).
Showing that fault-tolerant quantum computation is theoretically possible opened the way for attempts at practical realizations of quantum computers. See, e.g., E. Knill, R. Laflamme, and W. Zurek, Science, 279, p. 342 (1998). One proposed application of a quantum computer is factoring of large numbers. In such an application, a quantum computer could render obsolete all existing encryption schemes that use the “public key” method. In another application, quantum computers (or even a smaller scale device such as a quantum repeater) could enable absolutely safe communication channels where a message, in principle, cannot be intercepted without being destroyed in the process. See, e.g., H. J. Briegel et al., LANL preprint quant-ph/9803056 (1998).
Quantum computing generally involves initializing the states of N qubits (quantum bits), creating controlled entanglements among the N qubits, allowing the states of the qubit system to evolve, and reading the qubits afterwards. A qubit is conventionally a system having two degenerate (of equal energy) quantum states, with a non-zero probability of the system being found in either state. Thus, N qubits can define an initial state that is a combination of 2N classical states. This entangled initial state will undergo an evolution, governed by the interactions which the qubits have both among themselves and with external influences. This evolution defines a calculation, in effect 2N simultaneous classical calculations, performed by the qubit system. Reading out the qubits after evolution is complete determines their states and thus the results of the calculations.
Several physical systems have been proposed for the qubits in a quantum computer. One system uses molecules having degenerate nuclear spin states, see N. Gershenfeld and I. Chuang, “Method and Apparatus for Quantum Information Processing”, U.S. Pat. No. 5,917,322. Nuclear magnetic resonance (NMR) techniques can read the spin states. These systems have successfully implemented a search algorithm, see, e.g., M. Mosca, R. H. Hansen, and J. A. Jones, “Implementation of a quantum search algorithm on a quantum computer,” Nature, 393:344-346, 1998 and the references therein, and a number ordering algorithm, see, e.g., Lieven M. K. Vandersypen, Matthias Steffen, Gregory Breyta, Costantino S. Yannoni, Richard Cleve and Isaac L. Chuang, “Experimental realization of order-finding with a quantum computer,” Los Alamos preprint quant-ph/0007017 (2000). The number ordering algorithm is related to the quantum fourier transform, an essential element of both Shor's algorithm for factoring of a natural number and Grover's Search Algorithm for searching unsorted databases. However, efforts to expand such systems to a commercially useful number of qubits face difficult challenges.
One method for determining the state of a radio-frequency superconducting quantum interference device (RF-SQUID) qubit (another type of phase qubit) involves rapid single flux quantum (RSFQ) circuitry See Roberto C. Rey-de-Castro, Mark F. Bocko, Andrea M. Herr, Cesar A. Mancini, Marc J. Feldman, “Design of an RSFQ Control Circuit to Observe MQC on an rf-SQUID,” EEE Trans. Appl. Supercond, 11, 1014 (March 2001). A timer controls the readout circuitry and triggers the entire process with a single input pulse, producing an output pulse only for one of the two possible final qubits states. The risk of this readout method lies in the inductive coupling with the environment causing decoherence or disturbance of the qubit during quantum evolution. The readout circuitry attempts to reduce decoherence by isolating the qubit with intermediate inductive loops. Although this may be effective, the overhead is large, and the overall scalability is limited.
One physical implementation of a phase qubit involves a micrometer-sized superconducting loop with 3 or 4 Josephson junctions. See J. E. Mooij, T. P. Orlando, L. Levitov, Lin Tian, Caspar H. van der Wal, and Seth Lloyd, “Josephson Persistent-Current Qubit”, Science 1999 Aug. 13; 285: 1036-1039. The energy levels of this system correspond to differing amounts of magnetic flux threading the superconducting loop. Application of a static magnetic field normal to the loop may bring two of these levels (or basis states) into degeneracy. Typically, external AC electromagnetic fields are applied, to enable tunneling between non-degenerate states.
Further, currently known methods for entangling qubits also are susceptible to loss of coherence. Entanglement of quantum states of qubits can be an important step in the application of quantum algorithms. See for example, P. Shor, SIAM J. of Comput., 26:5, 1484-1509 (1997). Current methods for entangling phase qubits require the interaction of the flux in each of the qubits, see Yuriy Malhlin, Gerd Schon, Alexandre Shnirman, “Quantum state engineering with Josephson-junction devices,” LANL preprint, cond-mat/0011269 (November 2000). This form of entanglement is sensitive to the qubit coupling with surrounding fields which cause decoherence and loss of information.
As discussed above, currently proposed methods for readout, initialization, and entanglement of a qubit involve detection or manipulation of magnetic fields at the location of the qubit, which make these methods susceptible to decoherence and limits the overall scalability of the resulting quantum computing device. Thus, there is a need for an efficient implementation and method that minimizes decoherence and other sources of noise and maximizes scalability.